A flexible deterministic, stochastic and fuzzy Data Envelopment Analysis approach for supply chain risk and vendor selection problem: Simulation analysis

摘要

This study consists of three types of vendor selection models in supply chains and presents a decision making scheme for choosing appropriate method for supplier selection under certainty, uncertainty and probabilistic conditions. These models are, Data Envelopment Analysis (DEA), Fuzzy Data Envelopment Analysis (FDEA), and Chance Constraint Data Envelopment Analysis (CCDEA). In FDEA model we use α-cut method in five levels for α, to convert fuzzy DEA into interval programming. Also, we solve the CCDEA model for two levels of probabilities. It is assumed that inputs are random variables. Under this assumption the efficiency scores of Decision Making Units (DMUs) are random variables. Obtained results form each model is: average efficiency scores of DMUs, variance of efficiency scores, and 95% confidence interval for average. Results from three models are compared. Our decision making scheme allows decision makers to perform analysis among input factors which are expected costs, quality of acceptance levels, and on-time delivery. This is the first study to a present a flexible approach for supply chain risk and vendor selection. The superiority of the flexible algorithm is shown for 10 suppliers. Its features are also compared with previous models to show its advantages over previous models.